Evidence-driven agent skills for design award research, evaluation, matching, entry preparation, and submission checks across 11+ major design awards
Scanned 9/8/2026
Install to Claude Code
npx -y skills add Aradotso/design-skills --skill design-judge-skills --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Design Judge Skills?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/aradotso-design-judge-skills)More formats (shields.io, HTML) on the badges page.
---
name: design-judge-skills
description: Evidence-driven agent skills for design award research, evaluation, matching, entry preparation, and submission checks across 11+ major design awards
triggers:
- help me apply for design awards
- evaluate this design for award submission
- find similar award-winning designs
- which design award should I enter
- prepare my design award entry text
- check my award submission package
- design award pipeline workflow
- match my project to design awards
---
# design-judge-skills
> Skill by [ara.so](https://ara.so) — Design Skills collection.
`design-judge-skills` is a collection of modular agent skills that decompose the design award application process into discrete, verifiable workflows: award-winning case research, design evaluation, award matching, entry writing, and submission readiness checks.
The project covers 11 major design awards including iF DESIGN AWARD, Red Dot, IDEA, DIA, K-Design, GOOD DESIGN AWARD Japan, Core77, James Dyson Award, and EPDA. It includes observational data from **22,125 award-winning or finalist works** and enforces evidence-based evaluation with official source validation.
## Installation
### NPX Skills Installation (Recommended)
Requires [Node.js 18+](https://nodejs.org/).
**List available skills:**
```bash
npx skills add SeanJ1ang/design-judge-skills --list
```
**Install all skills globally for Codex:**
```bash
npx skills add SeanJ1ang/design-judge-skills --global --agent codex --skill '*' --yes --copy
```
**Install for Claude Code:**
```bash
npx skills add SeanJ1ang/design-judge-skills --global --agent claude-code --skill '*' --yes --copy
```
**Install a single skill with dependencies:**
```bash
# design-award-search and design-award-match require design-judge-shared
npx skills add SeanJ1ang/design-judge-skills --global --agent codex \
--skill design-award-search --skill design-judge-shared --yes --copy
```
**Install to all supported agents:**
```bash
npx skills add SeanJ1ang/design-judge-skills --all
```
**Check and update:**
```bash
npx skills list --global --agent codex
npx skills update --global --yes
```
### Manual Installation
For agents that support `SKILL.md` format:
1. Clone the repository to a stable path
2. Copy complete skill directories to your agent's skill directory
3. Preserve `SKILL.md`, `agents/`, `references/`, `scripts/`, `examples/`, and `tests/`
4. When installing `design-award-search` or `design-award-match`, also install `design-judge-shared`
## Skills Overview
The project provides 6 user-facing skills plus 1 shared support package:
| Skill | Status | Purpose |
|-------|--------|---------|
| `design-award-pipeline` | Beta | Orchestrates multi-stage award workflows and maintains handoff records |
| `design-award-search` | Stable | Retrieves and verifies similar award-winning cases from official sources |
| `design-evaluation` | Beta | Evaluates design quality and presentation with evidence-based scoring |
| `design-award-match` | Beta | Matches projects to awards, tracks, and categories with eligibility checks |
| `design-information-prep` | Beta | Extracts facts and prepares award entry text from user materials |
| `design-submission-check` | Beta | Validates submission packages against current official requirements |
| `design-judge-shared` | Support | Shared taxonomy and source registry (dependency only) |
## Workflow Patterns
### Complete Award Application Pipeline
```text
Use $design-award-pipeline to plan the complete award route from the provided materials and maintain stage handoff records.
```
The pipeline skill determines the minimal sufficient path based on user intent and current materials. It does NOT force execution of all stages.
### Finding Award-Winning Benchmarks
```text
Use $design-award-search to find officially verified award-winning cases similar to this rehabilitation training product.
```
**Key behaviors:**
- Searches official award galleries (iF, Red Dot, IDEA, etc.)
- Verifies each case by navigating to the official detail page
- Reports case metadata: award name, year, category, project title, designer, country
- Search summaries and third-party sites are used for discovery only
### Evaluating Design Quality
```text
Use $design-evaluation to evaluate the design in the attached files. I confirm the maturity level as "student concept". Output separate scores for design substance, presentation quality, evidence confidence, and critical issues.
```
**Maturity levels** (user must specify):
- `student-concept`: Conceptual work without market release
- `early-stage-product`: Pre-production or limited release
- `market-product`: Publicly available commercial product
**Evaluation dimensions:**
- Design substance (innovation, user value, feasibility, sustainability)
- Presentation quality (visual clarity, narrative logic, material completeness)
- Evidence confidence (factual vs. inferred vs. needs-user-confirmation)
- Critical issues (structural disqualifiers, misrepresentation risks, IP concerns)
**Example output structure:**
```markdown
## Design Substance: 7.8/10
- Innovation: 8/10 [evidence: novel mechanism in attached patent draft]
- User Value: 8/10 [evidence: user research summary p.3]
- Feasibility: 7/10 [inferred from CAD model; material sourcing not confirmed]
- Sustainability: 8/10 [evidence: LCA report attached]
## Presentation Quality: 6.5/10
- Visual Clarity: 7/10
- Narrative Logic: 6/10 [gap: user journey not visualized]
- Material Completeness: 6/10 [missing: technical specs diagram]
## Evidence Confidence: MEDIUM
- 60% factual (from attached documents)
- 25% model inference (from images and context)
- 15% needs user confirmation (material sourcing, certifications)
## Critical Issues: 2 items
1. [ELIGIBILITY] Production timeline unclear → may affect student vs. professional track
2. [EVIDENCE] Sustainability claim lacks third-party certification
```
Scores are for decision support only. They do NOT predict award probability.
### Matching Awards and Categories
```text
Use $design-award-match to compare award fit for iF Student, Red Dot Design Concept, DIA, Core77, and James Dyson for this project.
```
**Match outputs:**
- Structural eligibility (geographic, entity type, IP rights, timeline)
- Category recommendations with official taxonomy references
- Track selection (when applicable: student vs. professional, concept vs. product)
- Award fee, deadline (re-verified from official pages at runtime)
- Submission priority ranking with rationale
**Example snippet:**
```markdown
## iF DESIGN STUDENT AWARD
- Eligibility: ✓ PASS (student status confirmed, no geographic restriction)
- Best Category: 08 Health & Care → 08.03 Rehabilitation
- Fee: €0 (student track)
- Deadline: 2026-12-15 (re-verified from https://ifdesign.com/en/student-award)
- Priority: HIGH (strong alignment with evaluation criteria; no concept-stage penalty)
## Red Dot Design Concept
- Eligibility: ✓ PASS (concept stage accepted)
- Best Category: Living → Wellness & Healthcare
- Fee: €299 Early Bird / €399 Regular
- Deadline: 2026-10-31 Early / 2026-12-31 Regular
- Priority: MEDIUM (good fit but higher cost; consider after iF Student results)
```
### Preparing Entry Text
```text
Use $design-information-prep to prepare IDEA entry text from the attached materials. First list missing facts, then output English drafts with character count validation.
```
**Workflow:**
1. Extracts facts from user-provided documents (briefs, research, specs, images)
2. Reports missing mandatory fields for target award
3. Generates entry text drafts (title, description, innovation statement, etc.)
4. Validates character/word limits against official requirements
5. Tags each sentence with source attribution or `[INFERRED]` / `[USER CONFIRM]`
**Example output:**
```markdown
## Missing Information for IDEA Entry
- [ ] Project completion date (required)
- [ ] Retail price or production cost estimate
- [ ] Specific material certifications (referenced in sustainability claim)
## Draft: Project Title (max 100 chars)
**VitalGrip Rehabilitation Glove** [78 chars] ✓
## Draft: Design Innovation (max 500 words)
VitalGrip introduces a modular resistance system... [source: design brief p.2]
The sensor array provides real-time feedback... [source: technical spec diagram]
Preliminary user testing showed 40% improvement... [INFERRED from user research summary; USER CONFIRM exact metric]
[Draft continues...]
Word count: 487/500 ✓
```
### Submission Readiness Check
```text
Use $design-submission-check to validate this submission package against current Red Dot Product Design official requirements and provide a go/no-go recommendation.
```
**Check dimensions:**
- File format, resolution, size limits (re-verified from official submission guide)
- Mandatory vs. optional materials completeness
- Consistency across title, description, category, visual materials
- IP and rights declarations (model releases, trademark conflicts, authorship)
- Payment and entry form status
**Output format: go / conditional go / no-go**
```markdown
## Submission Check: Red Dot Product Design 2027
### File Compliance: ✓ PASS
- Main image: 3000×2250px JPG, 4.2MB ✓
- Supporting images (4): all 3000×2250px JPG ✓
- Video: MP4 1920×1080, 45s, 28MB ✓
### Content Completeness: ⚠ CONDITIONAL
- ✓ Project title, description, category
- ✓ Designer/company information
- ⚠ Innovation statement present but does NOT reference technical validation (recommended for this category)
- ✗ Sustainability documentation missing (required for "Sustainable Product" sub-category)
### Consistency Check: ✓ PASS
- Title matches across entry form and visual materials
- Category "01.03 Medical & Health" aligns with project scope
### Rights & IP: ⚠ CONDITIONAL
- ✓ Designer authorship declared
- ⚠ Model release for user testing photos not provided (required if faces visible)
## Recommendation: CONDITIONAL GO
**Action required before submission:**
1. Upload model release forms for user testing photos
2. Add technical validation reference to innovation statement (recommended)
3. Either remove "Sustainable Product" tag OR provide third-party certification
**Estimated fix time:** 2-4 hours
```
## Configuration & Data Sources
### Official Source Validation
Skills re-verify time-sensitive information (deadlines, fees, eligibility, format specs) at runtime by scraping official award pages. The `design-judge-shared/source-registry.md` maintains canonical URLs.
**Example source registry entry:**
```markdown
### iF DESIGN AWARD
- Main: https://ifdesign.com/en/design-award
- Submission Guide: https://ifdesign.com/en/submit
- Categories: https://ifdesign.com/en/categories
- Winners Gallery: https://ifdesign.com/en/winner-gallery
```
### Category Taxonomy
`design-judge-shared/category-taxonomy.md` maintains normalized category mappings across awards. Example:
```markdown
## Health & Medical Devices
- iF: 08 Health & Care
- Red Dot: Living → Wellness & Healthcare
- IDEA: Medical & Scientific Products
- DIA: Healthcare & Wellness
- K-Design: Medical & Health
```
### Observational Benchmark Data
Evaluation skills reference 22,125 aggregated observations from past winners (2015-2025) to provide descriptive context. This data:
- Does NOT alter core scoring logic
- Does NOT predict award probability
- Provides pattern recognition for presentation quality and category norms
- Is anonymized (no private project details)
See [benchmark coverage documentation](docs/benchmark-coverage.md) for privacy and limitation details.
## Environment Variables
No API keys or authentication required for basic functionality. Optional:
```bash
# For enhanced web scraping (if official sites use anti-bot measures)
export BROWSERLESS_API_KEY=your_key_here
# For bulk processing (optional concurrency limit)
export MAX_CONCURRENT_EVALUATIONS=5
```
## Common Patterns
### Pattern 1: Student Concept → Award Route
```python
# User provides: concept boards, research deck, CAD renderings
# Agent workflow:
# Step 1: Evaluate to confirm strengths and gaps
"Use $design-evaluation with maturity level 'student-concept'"
# Step 2: Match to student-friendly awards
"Use $design-award-match to compare iF Student, Red Dot Concept, Core77, James Dyson, and DIA for this student concept"
# Step 3: Prepare entry for top match
"Use $design-information-prep for iF DESIGN STUDENT AWARD"
# Step 4: Pre-submission check
"Use $design-submission-check for iF Student entry package"
```
### Pattern 2: Multi-Award Strategy
```python
# For a market product targeting multiple awards:
# Step 1: Find positioning benchmarks
"Use $design-award-search to find similar award winners in the smart home category from the past 3 years"
# Step 2: Evaluate against benchmark patterns
"Use $design-evaluation with maturity level 'market-product'"
# Step 3: Prioritize awards by fit and cost
"Use $design-award-match to compare iF, Red Dot Product, IDEA, DIA, K-Design, and GOOD DESIGN Japan"
# Step 4: Batch prepare entries for top 3
"Use $design-information-prep for iF DESIGN AWARD, Red Dot Product Design, and IDEA"
```
### Pattern 3: Pipeline Orchestration
```python
# When user says: "I have a rehabilitation glove concept and want to enter design awards"
"Use $design-award-pipeline to determine the optimal workflow and maintain handoff state"
# Pipeline decides minimal path, e.g.:
# 1. Evaluation (to assess readiness)
# 2. Award match (to select targets)
# 3. Information prep (for selected awards)
# 4. Submission check (before deadline)
# Pipeline maintains state file to resume or skip stages
```
## Troubleshooting
### Issue: Skill not triggering
**Solution:** After installation, start a NEW agent session to refresh skill registry. For Codex:
```bash
npx skills list --global --agent codex # verify installation
# Then restart Codex session
```
### Issue: "Missing design-judge-shared" error
**Solution:** Install the shared dependency:
```bash
npx skills add SeanJ1ang/design-judge-skills --global --agent codex \
--skill design-judge-shared --yes --copy
```
### Issue: Evaluation returns "insufficient evidence"
**Cause:** Missing or ambiguous design materials.
**Solution:** Provide at minimum:
- Visual materials (renderings, photos, or presentation boards)
- Project description (brief, design statement, or report)
- Maturity level confirmation from user
### Issue: Award match returns "eligibility unclear"
**Cause:** Missing structural information (student status, geographic location, IP ownership, production timeline).
**Solution:** Explicitly confirm:
- Entity type (student, startup, established company)
- Designer location (for geographic restrictions)
- IP ownership status
- Project completion date (for timeline-based eligibility)
### Issue: Official page scraping fails
**Cause:** Award website structure changed or anti-bot protection.
**Temporary workaround:** Manually verify deadline/fee from official site and provide to agent:
```text
I've verified from the official iF page: deadline is 2026-12-15, fee is €0 for students. Use this information for the match analysis.
```
**Long-term fix:** Report the issue at https://github.com/SeanJ1ang/design-judge-skills/issues with the affected award and URL.
### Issue: Character count validation fails
**Cause:** Award official requirement changed.
**Solution:** Cross-check the current submission guide link in `design-judge-shared/source-registry.md` and report discrepancy as an issue.
## Testing
Each skill includes example inputs and expected outputs in `skills/<name>/examples/` and automated tests in `skills/<name>/tests/`.
**Run tests for a specific skill:**
```bash
cd skills/design-evaluation
python tests/test_evaluation.py
```
**Run all tests:**
```bash
python run_all_tests.py
```
## Design Principles
1. **Official sources first:** Award rules and cases reference official pages; search summaries and third-party sites are for discovery only
2. **Separate fact from inference:** User materials, model inferences, and user-confirmation items are explicitly tagged
3. **Transparent scoring:** Fit scores and evaluation ratings support decisions but DO NOT predict award probability
4. **Single responsibility:** Skills do not cross boundaries (search ≠ evaluation ≠ matching ≠ prep ≠ check)
5. **No official impersonation:** Skills align with public criteria but do not simulate undisclosed judge preferences or internal processes
## Contributing
See [contribution guidelines](docs/CONTRIBUTING.md). Key points:
- Skill directory names match frontmatter `name` (kebab-case only)
- Core workflows stay in `SKILL.md`; long rules/specs go in `references/`
- Repeatable operations become `scripts/` with corresponding tests
- Do NOT commit API keys, cookies, user project materials, or copyrighted full case content
- Current year, deadlines, fees, and format specs must be runtime-verified from official sources
## License
Apache-2.0. See [LICENSE](LICENSE).
## Links
- Repository: https://github.com/SeanJ1ang/design-judge-skills
- Benchmark Coverage: [docs/benchmark-coverage.md](docs/benchmark-coverage.md)
- Skill Index: [README.md#6-技能索引](README.md#6-技能索引)
- English Documentation: [README_EN.md](README_EN.md)
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!